Checkpoint 1: EDA

By Arturo, Payson, and Victoria

Does healthcare access affect the number of preventable hospital stays of certain racial groups at the county level?

Why this matters:

  • Reduce preventable hospitalizations
  • Equitable resource allocation
  • Focus efforts where help is needed most

Data Overview

Source: County Health Rankings 2025

  • “Ranks every county in each state on their Health Outcomes and Health Factors”

Clinical Care

  • Preventable Hospital Stays (outpatient setting)
    • Providers (Primary Care, Physicans, Mental Health, Dentist)
    • Mammography Screening
    • Uninsured (Adults, Children)

Preventable Hospitalizations by County

Regression Analysis of Racial Disparities in Preventable Hospital Stays

Planned Approach:

  • Outcome: Preventable hospital stays
  • Predictors: Uninsured rate, provider ratio, race group

Modeling Strategy:

  • Explore variable selection and regularization

Moving into modeling and interpretation

Completed:

  • Defined research question
  • Cleaned and preprocessed dataset
  • Created initial EDA visualizations

Next Steps:

  • Fit regression models
  • Interpret disparities and validate model
  • Create visual summaries and poster